On the Estimation Performance of Generalized Power Method for Heteroscedastic Probabilistic PCA

no code implementations • 6 Dec 2023 • Jinxin Wang, Chonghe Jiang, Huikang Liu, Anthony Man-Cho So

The heteroscedastic probabilistic principal component analysis (PCA) technique, a variant of the classic PCA that considers data heterogeneity, is receiving more and more attention in the data science and signal processing communities.

Foundation Model is Efficient Multimodal Multitask Model Selector

1 code implementation • NeurIPS 2023 • Fanqing Meng, Wenqi Shao, Zhanglin Peng, Chonghe Jiang, Kaipeng Zhang, Yu Qiao, Ping Luo

This paper investigates an under-explored but important problem: given a collection of pre-trained neural networks, predicting their performance on each multi-modal task without fine-tuning them, such as image recognition, referring, captioning, visual question answering, and text question answering.

Model Selection Question Answering +1